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Nathan Harms is an Assistant Professor at the University of British Columbia specializing in theoretical computer science. His research focuses on understanding 'information' and the complexities involved in property testing and learning, as well as randomized communication. With a keen interest in how properties of functions can be tested more efficiently than learned, he emphasizes the distribution-free sample-based models. Harms has a background that straddles art and science, having transitioned from fine arts to theoretical computer science. He is also passionate about education and is looking to mentor Master’s and PhD students starting in 2026, urging interested candidates to submit their applications by December 15. Nathan received his academic training under Eric Blais at the University of Waterloo and later worked in Mika Göös' group at the École Polytechnique Fédérale de Lausanne.
Offers course-only and thesis routes. Focus areas include philosophy of science, mind, ethics, and Asian philosophy.